Time-stamped Data Feeds

Fast analysis of time series data is critical to your business.

Time, we seem to never have enough of it, but yet time series data is growing out of control. Time stamped data feeds are made up of any data that contains a time stamp. Common industry examples include:

eCommerce applications — store and analyze total value and delivery location of an order over time

This time series data analysis is critical to making good business decisions.

TIME-STAMPED DATA FEEDS ON RIAK TS

Time-stamped data feeds come in all shapes and sizes and the data is usually semi-structured. This requires a database that is optimized for time series data and is easy to analyze using range queries. Riak TS is a high performance, highly resilient NoSQL database optimized for fast reads and writes of time-stamped data feeds. Data co-location makes it fast to store time series data. This, along with the ability to create tables and perform SQL queries, makes it fast to analyze your time series data. Riak TS is operationally easy to use and allows you to add capacity on demand using commodity hardware. There is no need for complex data sharding.

WHY CUSTOMERS USE RIAK TS FOR TIME-STAMPED DATA FEEDS

Whether your data is a set of views and clicks, live social data, or financial market data, Riak TS optimally stores your time series data for fast analysis and real-time response. Riak TS’s masterless architecture, resiliency, linear scale, and operational simplicity are critical for ensuring your time series data is always available for read and write operations.

Retail & eCommerce companies use Riak TS to store time series data to track the value of an order, collect and analyze social metrics, or monitor truck locations and fuel usage.

Gaming & Betting companies use Riak TS to track user actions in their games and gather and analyze live social data for real-time decision making.